Software-Automated Counting of Ki-67 Proliferation Index Correlates With Pathologic Grade and Disease Progression of Follicular Lymphomas

Samols, Mark A.; Smith, Nathan; Gerber, Jonathan M.; Vuica‐Ross, Milena; Gocke, Christopher D.; Burns, Kathleen H.; Borowitz, Michael J.; Cornish, Toby C.; Duffield, Amy S.

doi:10.1309/ajcptma1f6lwytqv

Cited by 19 publications

(18 citation statements)

References 28 publications

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“…Noticeably, 12 different biological processes were significantly different between the studied FL groups, with cell cycle (higher in FL3B/DLBCL) and signal transduction (higher in FL1‐3A) reaching the highest statistical significance (Fig ) (Table SVII). Interestingly, cell proliferation is a relevant deregulated process with clinical impact in FL (Janikova et al , ; Samols et al , ; Kedmi et al , ). Our results suggested that changes in lncRNA expression between FL histological subgroups could contribute in part to the differential biological and clinical features by modulating the expression of proliferation‐related genes.…”

Section: Resultsmentioning

confidence: 99%

Differential expression of long non‐coding RNAs are related to proliferation and histological diversity in follicular lymphomas

Roisman

Castellano²,

Navarro

et al. 2018

Br J Haematol

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Long non-coding RNAs (lncRNAs) comprise a family of non-coding transcripts that are emerging as relevant gene expression regulators of different processes, including tumour development. To determine the possible contribution of lncRNA to the pathogenesis of follicular lymphoma (FL) we performed RNA-sequencing at high depth sequencing in primary FL samples ranging from grade 1-3A to aggressive grade 3B variants using unpurified (n = 16) and purified (n = 12) tumour cell suspensions from nodal samples. FL grade 3B had a significantly higher number of differentially expressed lncRNAs (dif-lncRNAs) with potential target coding genes related to cell cycle regulation. Nine out of the 18 selected dif-lncRNAs were validated by quantitative real time polymerase chain reaction in an independent series (n = 43) of FL. RP4-694A7.2 was identified as the top deregulated lncRNA potentially involved in cell proliferation. RP4-694A7.2 silencing in the WSU-FSCCL FL cell line reduced cell proliferation due to a block in the G1/S phase. The relationship between RP4-694A7.2 and proliferation was confirmed in primary samples as its expression levels positively related to the Ki-67 proliferation index. In summary, lncRNAs are differentially expressed across the clinico-biological spectrum of FL and a subset of them, related to cell cycle, may participate in cell proliferation regulation in these tumours.

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Section: Resultsmentioning

confidence: 99%

Differential expression of long non‐coding RNAs are related to proliferation and histological diversity in follicular lymphomas

Roisman

Castellano²,

Navarro

et al. 2018

Br J Haematol

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“…HIF-1α, VEGF, γ-H2A.X, annexin V, caspase-3, GAPDH, MCT4, LDH positivity was evaluated in the whole tumor area. The Aperio nuclear V9 algorithm was used to quantitatively identify Ki-67-positive cells as previously described (33, 37). …”

Section: Methodsmentioning

confidence: 99%

Preclinical Benefit of Hypoxia-Activated Intra-arterial Therapy with Evofosfamide in Liver Cancer

Durán

Mirpour

Pekurovsky

et al. 2017

Clinical Cancer Research

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Purpose To evaluate safety and characterize anticancer efficacy of hepatic hypoxia-activated intraarterial therapy (HAIAT) with evofosfamide in a rabbit model. Experimental Design VX2-tumor-bearing rabbits were assigned to 4 intraarterial therapy (IAT) groups (n=7/group): 1) saline (control); 2) evofosfamide (Evo); 3) doxorubicin-Lipiodol emulsion followed by embolization with 100-300μm beads (conventional, cTACE); or 4) cTACE and evofosfamide (cTACE+Evo). Blood samples were collected pre-IAT and 1/2/7/14 days post-IAT. A semiquantitative scoring system assessed hepatocellular damage. Tumor volumes were segmented on multidetector CT (baseline, 7/14 days post-IAT). Pathologic tumor necrosis was quantified using manual segmentation on whole slide images. Hypoxic fraction (HF) and compartment (HC) were determined by pimonidazole staining. Tumor DNA damage, apoptosis, cell proliferation, endogenous hypoxia and metabolism were quantified (γ-H2AX, annexin V, caspase-3, Ki-67, HIF1α, VEGF, GAPDH, MCT4 and LDH). Results cTACE+Evo showed a similar profile of liver enzymes elevation and pathologic scores compared to cTACE. Neither hematologic nor renal toxicity were observed. Animals treated with cTACE+Evo demonstrated smaller tumor volumes, lower tumor growth rates and higher necrotic fractions compared to cTACE. cTACE+Evo resulted in a marked reduction in the HF and HC. Correlation was observed between decreases in HF or HC and tumor necrosis. cTACE+Evo promoted antitumor effects as evidenced by increased expression of γ-H2A.X, apoptotic biomarkers and decreased cell proliferation. Increased HIF1α/VEGF expression and tumor glycolysis supported HAIAT. Conclusion HAIAT achieved a promising step towards the locoregional targeting of tumor hypoxia. The favorable toxicity profile and enhanced anticancer effects of evofosfamide in combination with cTACE pave the way towards clinical trials in patients with liver cancer.

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“…The authors also noted that digitally-obtained MIB-1 indices might correlate better with clinical outcome than the manually-counted value, but that further studies with larger sample sizes will be necessary to ascertain this. Notably, a recent study by Samols et al [4] examining follicular lymphoma showed that although a higher proliferative index in general correlated with a higher histologic grade, the authors identified a subset of low grade follicular lymphoma with a high proliferative index, a finding which itself had been previously reported by Wang et al (2005) [16]. This cohort reportedly showed a shorter overall survival, and Samols et al suggested that they should be considered as a different prognostic group compared with patients with follicular lymphoma whose proliferative fraction is low.…”

Section: Discussionmentioning

confidence: 99%

“…Importantly, automated image analysis has the potential to yield continuous variable data, unlike semi-quantitative analysis, which typically furnishes data in discrete increments. Many studies have shown digital quantification methods to demonstrate comparable accuracy to carefully performed formal manual quantification [4,9,10]. In this way, quantitative image analysis has the potential to objectively, accurately and consistently provide biomarker labelling indices, both in research and clinical settings [11].…”

Section: Journal Of Histology and Histopathology Issn 2055-091x | Volummentioning

confidence: 99%

“…For this reason it is used as a cellular marker for proliferation; the presence of nuclear staining indicates an active cycling cell.Having gained widespread use as a proliferation marker, MIB-1 has been shown to be a useful prognostic tool in several lymphoma subtypes. Numerous studies indicate that a high proliferation rate is associated with a more aggressive disease course, and hence a poorer prognosis [2][3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

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Quantitative image analysis of the MIB-1 proliferation index in Non-Hodgkin Lymphoma

Tchrakian¹,

Nehhozina²,

Lee³

et al. 2018

J Histol Histopathol

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Background: MIB-1 is a useful prognostic tool in Non-Hodgkin Lymphoma (NHL); in general, a high proliferative index (PI) is associated with aggressive disease. Quantitative image analysis (QIA) of tumour biomarkers has become more widespread due to the impractical nature of manual counting and the interobserver variability associated with semi-quantitative analysis.We hypothesized that a QIA algorithm would give a more accurate PI estimate, leading to better overall survival associations in cases of NHL. Methods: 51 MIB-1 immunohistochemical slides from NHL cases were scanned using Virtuoso image analysis software (Roche Tissue Diagnostics/Ventana), and the PI was digitally quantified using a nuclear algorithm from selected regions of interest. The diagnostic PI quantified by the pathologist was recorded from the original report and validated by both study pathologists. Medical records were reviewed and disease progression details and survival time noted. Results: Quantification of the MIB-1 index by image analysis showed strong positive correlation with the semi-quantified value(Spearman correlation coefficient =0.78; p<0.0001). Digitally-quantified MIB-1 proliferation indices demonstrated significance with overall survival in the lymphoma cohort (HR 1.6 (0.2-10.6); p=0.05) when compared with the semi-quantified values (HR 1.6 (0.2-10.6); p=0.6). Similarly digitally-quantified MIB-1 proliferation indices demonstrated significance with progression free survival in the lymphoma cohort (HR 2.8 (0.6-13.5); p=0.05) when compared with the semi-quantified values (HR 0.4 (0.2-1.2); p=0.1). Conclusions: QIA is a useful, reproducible and objective method of determining the MIB-1 PI in NHL cases and consideration should be given to introducing computer based algorithms into routine clinical haematopathology practice. However, QIA validation should be assessed in a larger sample cohort before consideration is given to introducing computer-based algorithms into routine clinical pathology practice.

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Software-Automated Counting of Ki-67 Proliferation Index Correlates With Pathologic Grade and Disease Progression of Follicular Lymphomas

Cited by 19 publications

References 28 publications

Differential expression of long non‐coding RNAs are related to proliferation and histological diversity in follicular lymphomas

Differential expression of long non‐coding RNAs are related to proliferation and histological diversity in follicular lymphomas

Preclinical Benefit of Hypoxia-Activated Intra-arterial Therapy with Evofosfamide in Liver Cancer

Quantitative image analysis of the MIB-1 proliferation index in Non-Hodgkin Lymphoma

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